2017
DOI: 10.1002/j.2334-5837.2017.00350.x
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MBSE Grid: A Simplified SysML‐Based Approach for Modeling Complex Systems

Abstract: After an organization makes the decision to adopt model‐based systems engineering (MBSE), it must go a long way before this decision proves right. There are many obstacles in this way, like stories about unsuccessful MBSE applications, insufficient information on how to proceed, and employee resistance to the cultural change to name a few. Neither of them is a true issue, if suitable enablers for MBSE adoption are chosen. Nowadays, MBSE is enabled by Systems Modeling Language (SysML). However, SysML is neither… Show more

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Cited by 60 publications
(32 citation statements)
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“…Analysis of MBSE methods and enterprise architecture frameworks reveals that the majority are conceptual and thus can hardly be used in combination with modeling languages, such as SysML, in practice. In contrast, the MBSE Grid approach proposed by (Morkevicius et al 2017), (Mazeika et al 2016) is fully compatible with SysML. Based on a transparent system architecture framework, it clearly defines the modeling process, reveals what model artefacts should be produced in each step of system lifecycle, and explains how to manage traceability relationships.…”
Section: Mbse Fundamental Conceptsmentioning
confidence: 99%
See 1 more Smart Citation
“…Analysis of MBSE methods and enterprise architecture frameworks reveals that the majority are conceptual and thus can hardly be used in combination with modeling languages, such as SysML, in practice. In contrast, the MBSE Grid approach proposed by (Morkevicius et al 2017), (Mazeika et al 2016) is fully compatible with SysML. Based on a transparent system architecture framework, it clearly defines the modeling process, reveals what model artefacts should be produced in each step of system lifecycle, and explains how to manage traceability relationships.…”
Section: Mbse Fundamental Conceptsmentioning
confidence: 99%
“…It is designed to guide system engineers through the modeling process by helping them answer questions, such as how to organize the model, what is the modeling workflow, what model artefacts should be produced in each step of that workflow, how these artefacts are linked together, etc. (Morkevicius et al 2017), (Morkevicius & Jankevicius 2015).…”
Section: Mbse Gridmentioning
confidence: 99%
“…MagicGrid is a SysML‐based framework for modeling complex systems. The MagicGrid framework consists of viewpoints (black box, white box, and solution) and aspects (the four pillars of SysML: requirements, system structure, system behavior, and parameters) organized in a grid view.…”
Section: State Of the Artmentioning
confidence: 99%
“…The MagicGrid framework consists of viewpoints (black box, white box, and solution) and aspects (the four pillars of SysML: requirements, system structure, system behavior, and parameters) organized in a grid view. The cells of the grid represent different views of MBSE, which are described as follows: (a) the requirement elicitation of stakeholders by using the SysML requirement (RE) diagram; (b) a use case description of the refinements of functional stakeholder needs; (c) system context representation using the SysML internal block diagram (IBD); (d) measures of effectiveness (MoEs), which indicate the nonfunctional requirements, described in the SysML block definition diagram (BDD). The MoEs calculation procedures are specified with the SysML parametric diagrams.…”
Section: State Of the Artmentioning
confidence: 99%
“…The International Council on Systems Engineering (INCOSE) defines Model-Based System Engineering (MBSE) as the formalized application of modeling to support system requirements, design, analysis, verification, and validation activities beginning in the conceptual design phase and continuing throughout development and later life cycle phases [1]. Today, MBSE and the SysML language have become an indispensable part of designing complex cyber-physical systems [2][3][4]. The reasons for their popularity are [1-4]:…”
Section: Introductionmentioning
confidence: 99%